Hemispheric asymmetries for music and speech: Spectrotemporal modulations and top-down influences
Bibliographic record
Abstract
Hemispheric asymmetries in auditory cognition have been recognized for a long time, but their neural basis is still debated. Here I focus on specialization for processing of speech and music, the two most important auditory communication systems that humans possess. A great deal of evidence from lesion studies and functional imaging suggests that aspects of music linked to the processing of pitch patterns depend more on right than left auditory networks. A complementary specialization for temporal resolution has been suggested for left auditory networks. These diverse findings can be integrated within the context of the spectrotemporal modulation framework, which has been developed as a way to characterize efficient neuronal encoding of complex sounds. Recent studies show that degradation of spectral modulation impairs melody perception but not speech content, whereas degradation of temporal modulation has the opposite effect. Neural responses in the right and left auditory cortex in those studies are linked to processing of spectral and temporal modulations, respectively. These findings provide a unifying model to understand asymmetries in terms of sensitivity to acoustical features of communication sounds in humans. However, this explanation does not account for evidence that asymmetries can shift as a function of learning, attention, or other top-down factors. Therefore, it seems likely that asymmetries arise both from bottom-up specialization for acoustical modulations and top-down influences coming from hierarchically higher components of the system. Such interactions can be understood in terms of predictive coding mechanisms for perception.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".